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The tool helps biologists and bioinformaticians mine large amount of prokaryotic comparative genomics data and explore the landscape of both conserved and idiosyncratic genomic regions across multiple genomes. Domains of application of these analyses are diverse: identification of evolutionary events, inference of gene functions, detection of niche-specific genes or phylogenetic profiling. Insyght combines three complementary displays:

(i) a table for thoroughly browsing amongst homologues,

(ii) a comparator of orthologue functional annotations and

(iii) a genomic organization view designed to improve the legibility of rearrangements and distinctive loci.

Synchronized navigation across multiple species and interoperability between the views are core features of Insyght. A gene filter mechanism is provided that helps the user to build a biologically relevant gene set according to multiple criteria such as presence/absence of homologues and/or various annotations.
 

The name PAREO is short for "PAthway Relational Organisation".
Actually, PAREO is mainly based on KEGG (*) data, but these data are stored within our own relationnal database hosted at MIG unit, allowing special processings which are briefly described below.

Within PAREO Web interface, you can browse pathways, enzymes, compounds or species through hierarchical treeviews.
When displaying KEGG's pathway map, PAREO can colorize enzyme boxes according to the existence of a corresponding gene within the specie's annotated genome.
And it is possible to colorize a map for many species at the same time (by many, we mean less than a dizain, otherwise it's difficult to see anything!).

Moreover you can define your own group of species : then the color intensity of the box will reflect the number of occurence of a corresponding gene amongst the species of the group.
Finally, if your favorite species is not yet fully sequenced and/or annotated, you can define a (private) fictive species and associate a list of EC to it. Then, you will be able to use it as any other species to colorize enzyme boxes.

You can also add some comment on any pathway, enzyme, compound or gene, which will be shared with all PAREO users.
Of course, these comments are kept up between PAREO updates.

(*) Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., and Hirakawa, M.; From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 34, D354-357 (2006).

Ensemble d'outils informatiques et de bases de connaissances pour la recherche et l’extraction d’information basées sur l'analyse sémantique automatique de documents à caractère scientifique ou technique.

Alvis comprend différents composants indépendants et interopérables :

• AlvisNLP/ML : Chaîne de traitement linguistique et sémantique automatique paramétrable.
• AlvisIR : Plateforme de construction de moteurs de recherche sémantiques.
• TyDI : Interface de validation et de construction de terminologies et termino-ontologies.
• AlvisAE : Interface collaborative d'annotation sémantique de documents.
• BioYaTeA : Extracteur automatique de termes adapté aux documents en biologie.
• AlvisCrawler : Aspirateur de documents scientifiques.
• SPSK : Extracteur automatique de relations dans des documents.
• CoCitations : Base de Données de cocitations de gènes dans des abstracts PubMed.

The term entered should be an exact entry name from SwissProt or a complete accession number. You will have access to all the information about the protein.

The Erdös–Rényi model of a network is simple and possesses many explicit expressions for average and asymptotic properties, but it does not fit well to real-world networks. The vertices of those networks are often structured in unknown classes (functionally related proteins or social communities) with different connectivity properties. The stochastic block structures model was proposed for this purpose in the context of social sciences, using a Bayesian approach. We consider the same model in a frequentest statistical framework. We give the degree distribution and the clustering coefficient associated with this model, a variational method to estimate its parameters and a model selection criterion to select the number of classes. This estimation procedure allows us to deal with large networks containing thousands of vertices. The method is used to uncover the modular structure of a network of enzymatic reactions.

The B. subtilis Expression Data Browser contains summarised information of tiling array log2-expression data in different growth conditions (Highest Expression Conditions, Most Positively Correlated Segments, Expression Profile, Annotation, Genomic View of Gene/Segment, ...) acquired during BaSysBio european project (2006-2010, [Nicolas et. al, Science 2012]).

CoCitation searches for lists of genes or proteins names that are cocited in PubMed references. The names and synonyms of the genes and proteins of the model bacterium Bacillus subtilis are taken from the general databases SwissProt, GenBank, and from the dedicated database Subtiwiki.

The user first selects the gene or protein names to be searched. The cocitations may be then searched either within sentences or in the whole references, titles and abstracts. The biological meaning of the cocitation, e.g. interaction, binding, homology is automatically inferred by the CoCitation tool so that focused biological knowledge can be quickly derived by the user. The textual information can be integrated with experimental data through IGo, by simple click on the IGo icon or name.

CoCitation is a software developed by the INRA MIG laboratory. It is also accessible through the on-line portal IGo. It is based on the research of the MIG Bibliome team. It has been financially supported by the Quaero project.

Ensemble d'outils informatiques et de bases de connaissances pour la recherche et l’extraction d’information basées sur l'analyse sémantique automatique de documents à caractère scientifique ou technique.

Alvis comprend différents composants indépendants et interopérables :

• AlvisNLP/ML : Chaîne de traitement linguistique et sémantique automatique paramétrable.
• AlvisIR : Plateforme de construction de moteurs de recherche sémantiques.
• TyDI : Interface de validation et de construction de terminologies et termino-ontologies.
• AlvisAE : Interface collaborative d'annotation sémantique de documents.
• BioYaTeA : Extracteur automatique de termes adapté aux documents en biologie.
• AlvisCrawler : Aspirateur de documents scientifiques.
• SPSK : Extracteur automatique de relations dans des documents.
• CoCitations : Base de Données de cocitations de gènes dans des abstracts PubMed.

Corpus and ontologies are distributed under the Creative Commons CC-BY-SA license

• Corpus LLL (Learning Language is Logic): the corpus is the original corpus of the LLL challenge. The goal of the LLL challenge is to evaluate the ability of the participating Information Extraction systems to identify directed interactions and the gene/proteins that interact (the named entities must detected). The on-line evaluation service is still available. Note that the LLL corpus differs from the BioInfer LLL corpus. The Bioinfer corpus is a transformation of the original LLL corpus where the IE task has been made much easier: the relation arguments are given and the relation is not directed.

• Corpus BI : the corpus is part of the Bacteria Interaction task in the BioNLP Shared Task 2011. The goal is to extract complex interaction events from Pubmed references.

• Corpus GRN : the corpus is part of the Gene Regulation Network in Bacteria task in the BioNLP Shared Task 2013. The goal is to extract the full regulation network of Bacillus subtilis sporulation. The on-line evaluation service is still available.

• Corpus BB'11 : the corpus is part of the Bacteria Biotope Task in the BioNLP Shared Task 2011. The goal is (1) to identify the bacteria and their habitat that have to be categorized in seven different types and (2) to extract relations between bacteria and their habitat.

• Corpus BB'13 : the corpus is part of the Bacteria Biotope Task in the BioNLP Shared Task 2011. The goal is (1) to identify the bacteria and their habitat that have to be categorized by the concept of the OntoBiotope ontologies and (2) to extract relations between bacteria and their habitat. The on-line evaluation service is still available.

• Ontologie OntoBiotope : The ontology OntoBiotope describes microorganismes habitats in the form of hierarchy. It contains 1700 concepts in Obo format.

• ATOL Ontology : The Animal Trait Ontology for Livestock describes the characters of livestock animals.

The main question R'MES addresses is "does this motif occur in that biological sequence with an expected frequency?" In other words, can we observe it so many times, or so few times, just by chance? Usually, when the answ er is no, such a motif is a candidate to have a particular biological meaning; only a candidate: statistical significance is not equivalent to biological significance.

Computation of sensitivity indexes by using a method based on a truncated Polynomial Chaos Expansion of the response and regression PLS, for computer models with correlated continuous inputs, whatever the input distribution. T he truncated Polynomial Chaos Expansion is built from the multivariate Legendre orthogonal polynomials. The number of runs (rows) can be smaller than the number of monomials. It is possible to select only the most significa nt monomials. Of course, this package can also be used if the inputs are independent. Note that, when they are independent and uniformly distributed, the package 'polychaosbasics' is more appropriate.

Computation of sensitivity indexes by using a method based on a truncated Polynomial Chaos Expansions of the response. The necessary condition of the method is: the inputs must be uniformly and independently sampled. Since the inputs are uniformly distributed, the truncated Polynomial Chaos Expansion is built from the multivariate Legendre orthogonal polynomials.

The sivipm R package computes total and individual sensitivity indices, significant components, and confidence intervals for the total sensitivity indices. The total and individual sensitivity indices are calculated using a method based on the VIP of the PLS regression, proposed by J.P. Gauchi. The significant components are calculated by the SIMCA software rule and by the Lazraq & Cléroux test. The confidence intervals for the total sensitivity indices are determined by the bootstrap method.

The functions proposed in this package compute the density of the sum of a Gaussian and a gamma random variables, estimate the parameters and correct the noise effect in a gamma-signal and Gaussian-noise model. This package has been used to implement the background correction method for Illumina microarray data presented in Plancade S., Rozenholc Y. and Lund E. "Generalization of the normal-exponential model : exploration of a more accurate parameterization for the signal distribution on Illumina BeadArrays", BMC Bioinfo 2012, 13(329).

The parameter estimation is performed in the maximum-likelihood (ML) sense. IDEAS offers several options for the optimal criterion, depending on the hypothesis on the covariance matrix of the measurement errors.

WACSgen is a single-site, stationary multivariate weather generator for daily climate variables based on weather-states that uses a Markov chain for modeling the succession of (an unlimited number of) weather states. Conditionally to the weather states, the multivariate variables are modeled using the family of Complete skew-normal distributions.